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qRAT: an R-based stand-alone application for relative expression analysis of RT-qPCR data
BACKGROUND: Reverse transcription quantitative real-time PCR (RT-qPCR) is a well-established method for analysing gene expression. Most RT-qPCR experiments in the field of microbiology aim for the detection of transcriptional changes by relative quantification, which means the comparison of the expr...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9297597/ https://www.ncbi.nlm.nih.gov/pubmed/35854213 http://dx.doi.org/10.1186/s12859-022-04823-7 |
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author | Flatschacher, Daniel Speckbacher, Verena Zeilinger, Susanne |
author_facet | Flatschacher, Daniel Speckbacher, Verena Zeilinger, Susanne |
author_sort | Flatschacher, Daniel |
collection | PubMed |
description | BACKGROUND: Reverse transcription quantitative real-time PCR (RT-qPCR) is a well-established method for analysing gene expression. Most RT-qPCR experiments in the field of microbiology aim for the detection of transcriptional changes by relative quantification, which means the comparison of the expression level of a specific gene between different samples by the application of a calibration condition and internal reference genes. Due to the numerous data processing procedures and factors that can influence the final result, relative expression analysis and interpretation of RT-qPCR data are still not trivial and often necessitate the use of multiple separate software packages capable of performing specific functions. RESULTS: Here we present qRAT, a stand-alone desktop application based on R that automatically processes raw output data from any qPCR machine using well-established and state-of-the-art statistical and graphical techniques. The ability of qRAT to analyse RT-qPCR data was evaluated using two example datasets generated in our laboratory. The tool successfully completed the procedure in both cases, returning the expected results. The current implementation includes functionalities for parsing, filtering, normalizing and visualisation of relative RT-qPCR data, like the determination of the relative quantity and the fold change of differentially expressed genes as well as the correction of inter-plate variation for multiple-plate experiments. CONCLUSION: qRAT provides a comprehensive, straightforward, and easy-to-use solution for the relative quantification of RT-qPCR data that requires no programming knowledge or additional software installation. All application features are available for free and without requiring a login or registration. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-022-04823-7. |
format | Online Article Text |
id | pubmed-9297597 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-92975972022-07-21 qRAT: an R-based stand-alone application for relative expression analysis of RT-qPCR data Flatschacher, Daniel Speckbacher, Verena Zeilinger, Susanne BMC Bioinformatics Software BACKGROUND: Reverse transcription quantitative real-time PCR (RT-qPCR) is a well-established method for analysing gene expression. Most RT-qPCR experiments in the field of microbiology aim for the detection of transcriptional changes by relative quantification, which means the comparison of the expression level of a specific gene between different samples by the application of a calibration condition and internal reference genes. Due to the numerous data processing procedures and factors that can influence the final result, relative expression analysis and interpretation of RT-qPCR data are still not trivial and often necessitate the use of multiple separate software packages capable of performing specific functions. RESULTS: Here we present qRAT, a stand-alone desktop application based on R that automatically processes raw output data from any qPCR machine using well-established and state-of-the-art statistical and graphical techniques. The ability of qRAT to analyse RT-qPCR data was evaluated using two example datasets generated in our laboratory. The tool successfully completed the procedure in both cases, returning the expected results. The current implementation includes functionalities for parsing, filtering, normalizing and visualisation of relative RT-qPCR data, like the determination of the relative quantity and the fold change of differentially expressed genes as well as the correction of inter-plate variation for multiple-plate experiments. CONCLUSION: qRAT provides a comprehensive, straightforward, and easy-to-use solution for the relative quantification of RT-qPCR data that requires no programming knowledge or additional software installation. All application features are available for free and without requiring a login or registration. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-022-04823-7. BioMed Central 2022-07-19 /pmc/articles/PMC9297597/ /pubmed/35854213 http://dx.doi.org/10.1186/s12859-022-04823-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Software Flatschacher, Daniel Speckbacher, Verena Zeilinger, Susanne qRAT: an R-based stand-alone application for relative expression analysis of RT-qPCR data |
title | qRAT: an R-based stand-alone application for relative expression analysis of RT-qPCR data |
title_full | qRAT: an R-based stand-alone application for relative expression analysis of RT-qPCR data |
title_fullStr | qRAT: an R-based stand-alone application for relative expression analysis of RT-qPCR data |
title_full_unstemmed | qRAT: an R-based stand-alone application for relative expression analysis of RT-qPCR data |
title_short | qRAT: an R-based stand-alone application for relative expression analysis of RT-qPCR data |
title_sort | qrat: an r-based stand-alone application for relative expression analysis of rt-qpcr data |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9297597/ https://www.ncbi.nlm.nih.gov/pubmed/35854213 http://dx.doi.org/10.1186/s12859-022-04823-7 |
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